Lead Data Scientist (P3764)

84.51° • Cincinnati, OH

14d • $125,000 - $207,000 • Onsite

About The Position

Relevancy Sciences Team is responsible for powering relevant, personalized, and scalable customer experiences across Kroger’s e-commerce ecosystem. We build and evolve the science behind search and recommendations that serve millions of customers and support high-scale digital experiences.

We are seeking a Lead Data Scientist to provide technical leadership across search and recommender systems, with a strong focus on modern model architectures, and production-ready machine learning. This role is ideal for someone who combines depth in applied machine learning with strong systems thinking, cross-functional influence, and contributes towards agentic capabilities.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 6+ years applied ML with explicit search and/or recommendation systems experience.
• Demonstrated experience designing and building systems at scale — including representation learning, candidate retrieval and ranking with multi-stage pipelines
• Proficient in Python and SQL, with experience processing large-scale data in distributed environments (e.g., Spark).
• Track record of shipping ML systems that moved business or customer metrics at scale – not just exposure to frameworks or techniques.
• Strong foundation in statistics, experimentation, and data analysis, including design of experiments and A/B testing.
• Hands-on experience building or rigorously evaluating LLM- and agent-based systems (e.g., RAG, agentic workflows, LLM-based evaluation), with clear judgment on where these techniques apply and where they don't.
• Experience partnering with engineering teams to deploy and maintain machine learning systems in production.
• Understanding of real-time systems, model serving, feature pipelines, and monitoring.
• Ability to make practical tradeoffs between model complexity, performance, latency, and scalability.
• Demonstrated ability to lead technical work across projects and influence direction across data science, engineering, and product teams.
• Experience mentoring or guiding other data scientists and contributing to a strong technical culture.
• Experience working with cloud platforms such as GCP or Azure.
• Experience in retail, e-commerce, or high-scale consumer domains is a plus.

Nice To Haves

• Experience in retail, e-commerce, or high-scale consumer domains is a plus.

Responsibilities

• Own and drive technical initiatives across search & recommender systems. Define and evolve the science strategy for improving content discovery, relevance, personalization, and decision support across digital experiences. Identify high-impact opportunities, make clear technical tradeoffs, and guide the team towards scalable, practical solutions. Rapidly prototype and validate new ideas to accelerate adoption and demonstrate measurable value.
• Design and build ML solutions tailored to the unique needs of grocery retail domain. Lead the development of systems that improve product discovery and personalization across customer journeys. Bring strong technical and thought leadership on next generation personalization, including the use of Generative AI and agent-based approaches.
• Establish rigorous evaluation methodologies to assess the performance of ML systems across key metrics. Define robust online evaluation frameworks, and guide experimentation strategies that connect model improvements to customer and business outcomes.
• Partner closely with Engineering to build and deploy production-ready ML systems. Influence design decisions related to real-time inference, feature access, system integration, monitoring, and reliability. Ensure solutions meet latency, scalability, and operational requirements. Contribute to the evolution of serving and deployment strategies.
• Work closely with Product, Engineering, and business stakeholders to translate needs into clear problem statements, hypotheses, and execution plans. Drive alignment across teams and influence decisions through clear communication of tradeoffs, risks, and expected outcomes.
• Mentor data scientists and lead technical reviews to improve model quality, experimentation rigor, and systems thinking. Promote best practices in reproducibility and evaluation. Contribute to building a strong, learning-oriented team culture.

Benefits

• Medical: with competitive plan designs and support for self-care, wellness and mental health.
• Dental: with in-network and out-of-network benefit.
• Vision: with in-network and out-of-network benefit.
• 401(k) with Roth option and matching contribution.
• Health Savings Account with matching contribution (requires participation in qualifying medical plan).
• AD&D and supplemental insurance options to help ensure additional protection for you.
• Paid time off with flexibility to meet your life needs, including 5 weeks of vacation time, 7 health and wellness days, 3 floating holidays, as well as 6 company-paid holidays per year.
• Paid leave for maternity, paternity and family care instances.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior